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SBIR/STTR

NonLinear Parallel OPtimization Tool, Phase I

Project Introduction

CU Aerospace, in partnership with the University of Illinois propose the further development of a new sparse nonlinear programming architecture that exploits parallelism at three levels. The Nonlinear Parallel Optimization Tool (NLPAROPT) is a black-box NLP solver intended to take advantage of multicore processors and distributed processing super computers alike to vastly improve the time-to-solution for optimization problems. It has been built with NASA trajectory optimization problems in mind, but can be applied to any class of NLP problem. By parallelising not only the basic linear algebra, but also the derivative calculation, problem formulation, and sparse aspects of typical problems, significant speed improvements are achievable by comparison to existing open source and commerical NLP solvers.
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Anticipated Benefits

NASA currently utilizes SNOPT, IPOPT, and WORHP software packages for astrodynamics applications such as the design of complex spacecraft trajectories and other optimal control problems, but could greatly benefit from the introduction of a new parallel large-scale, nonlinear, sparse optimization solution. This new parallelized NLP technique has already been shown to result in a reduction in execution time, thereby reducing the optimization's turn-around time and improve communications between both designers and scientists. Our solver would act as a significant force multiplier for existing NASA tools such as GMAT's collocation-based low-thrust transcription, and EMTGs inner loop solver.

Any group which needs to take advantage of nonlinear program problem optimization will benefit from the improved time-to-solution provided by NLPAROPT. There are direct applications to engineering design for other government agencies such as DoD who could use it in logistics optimziation, or NOAA who could use it for weather modelling. The DOE could use it for power grid optimization, and the USDA could use it for crop planting strategies. Further, most large aerospace corporations have internal optimization tools that depend on black-box solvers; NLPAROPT could substitute for those solvers and significantly improve the existing tools used in industry.
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